Research map / Label-efficient and robust learning / Recognition and long-tail
Nested Named Entity Recognition as Building Local Hypergraphs
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Build local hypergraphs bidirectionally and merge predictions (ablation) | LHBN · ACE04 | F1: 88.09 -> 88.46 | Helped |
| Build local hypergraphs bidirectionally and merge predictions (ablation) | LHBN · ACE04 | F1: 87.50 -> 88.46 | Helped |
| Add a separate encoder for boundary tokens (ablation) | LHBN · ACE04 | F1: 87.73 -> 88.46 | Helped |
| Initialize the hypergraph-builder LSTM with boundary representations (ablation) | LHBN · ACE04 | F1: 88.02 -> 88.46 | Helped |
Closest papers by meaning
- Recursively Binary Modification Model for Nested Named Entity Recognition (AAAI 2020 · similarity 0.86)
- Span Graph Transformer for Document-Level Named Entity Recognition (AAAI 2024 · similarity 0.85)
- Small Language Model Makes an Effective Long Text Extractor (AAAI 2025 · similarity 0.84)
- MCL-NER: Cross-Lingual Named Entity Recognition via Multi-View Contrastive Learning (AAAI 2024 · similarity 0.83)
- GuideNER: Annotation Guidelines Are Better than Examples for In-Context Named Entity Recognition (AAAI 2025 · similarity 0.83)
- SENCR: A Span Enhanced Two-Stage Network with Counterfactual Rethinking for Chinese NER (AAAI 2024 · similarity 0.83)
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